Biomacromolecules 2000, 1, 721-729
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Interpenetrating Network Formation in Gellan-Agarose Gel Composites E. Amici, A. H. Clark,* V. Normand, and N. B. Johnson Unilever Research Colworth, Colworth Laboratory, Sharnbrook, Bedford MK44 1LQ, U.K. Received June 16, 2000; Revised Manuscript Received August 29, 2000
Thermal, mechanical, turbidity, and microscope evidence is provided which strongly suggests molecular interpenetrating network (IPN) formation by mixtures of the bacterial and seaweed polysaccharides gellan and agarose. There is no evidence for synergistic coupling of the networks, and simple phase separation (demixing) can definitely be ruled out. Some changes in the gellan gelling behavior are suggested, however, by the increased gellan effective concentrations implicit in cure curve data. The dependence of this effect on the agarose nominal concentration seems consistent with a previous model that focused on gelling parameters, and changes in these, rather than real concentration effects. In large deformation mechanical tests, the influence of agarose added to gellan is to re-enforce the network (higher compression and shear moduli, higher stresses-to-break) without significantly changing the strain to break, or the gellan brittle failure mechanism. Introduction Gels based on aqueous biopolymer mixtures1 have become important subjects for study during the past decade mainly because of their increasing value in a number of practical applications (particularly in the food industry). They present interesting scientific challenges in areas such as polymer solution behavior, network formation, and gel materials science. A complex blend of kinetic and thermodynamic issues is involved, with the large volume of water usually present introducing extra complexity in relation to the more commonly discussed features of synthetic polymer mixtures. These two areas have many aspects in common, however: the study of biopolymer mixtures owes much of its foundation to ideas and techniques discussed in the synthetic polymer blend literature. The simplest type of mixed biopolymer gel is that in which sizable inclusions of one gel phase reside as spherical droplets inside a gelled matrix. This situation arises when a waterin-water emulsion formed from an initially unstable mixed biopolymer solution is gelled thermally (temperature jump, ramp, etc.). Features of such gels which distinguish them from synthetic polymer counterparts based on blends (absence of solvent) are the polymer concentration effects achieved in the separated phases2-4 and the physical nature of the network cross-links (neither topological entanglements nor covalent bonds but physical associations of intermediate strength and permanence). Variations in structures of this type, also found, include situations where the droplets connect and percolate, either as bonded gelled particles or through fusion into an interpenetrating phase (bicontinuous system). This last tends to happen when phase volumes approximate the 50:50 situation, and where the pre-gelling phase viscosities and/or the interfacial surface tension values are favorable. Theoretical models have been developed for
these “emulsion” gels, particularly in relation to their linear mechanical properties.2-4 A rather different situation occurs when the original biopolymer mixture resists liquid-liquid demixing (e.g., as can happen where an uncharged polymer combines with a significantly charged one, through the so-called counterion entropy effect5) and where this resistance persists even at the point of molecular conformational change, aggregation, and gelation. In this case, while microphase-separated systems analogous to the emulsion gels can still form, if demixing competes successfully with gelation, it is also possible to obtain molecularly interpenetrating networks (molecular IPN’s) for which a phase-separated description seems inappropriate. As an example, a previous paper6 has described molecular interpenetration of networks based on the biopolymers gellan (a bacterial polysaccharide) and Paselli SA2 (an enzyme hydrolyzed potato starch). This previous article presented structural and rheological data supporting the idea of molecular interpenetration, and discussed changes needed to models to describe these types of situations and materials. A complication which emerged, was that the starch gel was itself microphase separated, even in the “natural” unmixed form. This resulted in the final mixed gel structure, of micrometer-sized starch microgel regions, embedded in a gellan matrix, and apparently interpenetrated by the gellan network, being a less than perfect example of a molecular IPN. The present paper seeks to study a simpler, and hopefully more ideal, case of molecular IPN formation, by describing a mixed gel system based on two biopolymer components, neither of which shows significant inhomogeneity in its individual network structure. This new combination again involves the bacterial polysaccharide gellan,6,7 but this time in association with the largely uncharged marine (seaweed) polysaccharide agarose.7 As in the gellan-Paselli SA2 case,
10.1021/bm000057d CCC: $19.00 © 2000 American Chemical Society Published on Web 09/29/2000
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the charged-uncharged polymer counterion entropy effect is again relied upon to promote solution homogeneity, with this and the rapid gelling kinetics of the two biopolymers below their gelation temperatures tending to maintain homogeneity at the point of gelation. Again, both structural and mechanical data will be presented, with the addition this time of results from differential scanning calorimetry (DSC), and reference will be made to modeling ideas introduced in the previous article. Materials and Methods Materials. Gellan7 is an extracellular polysaccharide produced by the bacterium Sphingomonas (sometimes Pseudomonas) elodea. It is a linear anionic heteropolysaccharide based on a tetrasaccharide repeat unit of glucose, glucuronic acid, and rhamnose and forms cold-set gels based on aggregation of ordered double helices. A sample was obtained in mixed salt form from Kelco (Kelcogel F). The ion content was (by weight) 3.96% K+, 0.64% Na+, 0.3% Ca2+, and 0.12% Mg2+ as determined by atomic absorption. The molecular mass distribution was determined in the coil form at 60 °C using size exclusion chromatography and light scattering. Columns (Anagel-TSK PWXL G4000, G5000, and G6000 in series) were eluted at 60 °C with 0.1 M LiCl (0.5 mL/min) and light scattering detected using a DAWN-F MALLS photometer (Wyatt Technology) equipped with a He-Ne laser (633 nm, 5 mW). Calibration of equipment involved toluene and pullulan standards and the gellan refractive index increment assumed was 0.147. Molecular weight averages determined were Mw ) 1.8 × 105 and Mn ) 1.0 × 105. Agarose7 (a major constituent of agar) originates in red seaweeds (Rhodophyceae) and is a linear uncharged polymer with an idealized structure based on a disaccharide repeat unit consisting of (1-3)-linked β-D-galactose and (1-4)linked 3,6-anhydro-R-L-galactose. Like gellan it forms coldset gels based on aggregation of ordered double helices. The sample used here was purchased from Sigma (type 1-A, low EEO, A-0169). The sulfate content was less than 0.2% w/w. Molecular weight averages were obtained in the same manner as for gellan, and were Mw ) 1.7 × 105 and Mn ) 1.0 × 105. Solutions were prepared by accurate weighing of components at ambient temperature and heating to the boiling point for 25 min with stirring. NaCl, in the amount necessary to fix the ionic strength (0.066 M), was added separately in solution form, after 15 min. Small-Deformation Rheology. Measurements of storage and loss shear moduli (G′,G′′) were performed on a Carrimed CSL 500 stress-controlled rheometer using a coaxial cylinder geometry (internal radius 20 mm, external 23 mm, gap 3 mm). Hot solutions were introduced between the cylinders. They were supported at the bottom by a layer of perfluorodecaline and sealed at the top with silicone oil. Experiments were performed at a constant frequency of 1 Hz and at 0.5% strain, using temperature programs to be specified in later sections (programmable circulating water bath). Large-Deformation Compression Testing. Measurements of the compressive strength of the gels were performed
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under uniaxial compression, on an Instron Universal testing machine (model 4502) using a parallel plate geometry. Test parameters were as follows: load cell 0.100 kN, crosshead speed 50 mm/min, and sampling rate 10 points/s. Hot solutions were poured into cylindrical molds (12.2 mm length and 12.5 mm diameter), allowed to gel at room temperature, and stored at 5 °C for 20 h. Before loading on to the Instron the samples were equilibrated at room temperature for 2 h. Between 8 and 10 replicates were tested for each composition considered. Corrected true stress and strain were calculated as FH/AoHo and -ln(H/Ho) where H was the varying specimen height, Ho its original height, Ao its original crosssection, and F the applied load. Compressive elastic moduli were calculated from the initial linear parts of the stressstrain curves (strain less than 0.05) in the usual way. Differential Scanning Calorimetry. Measurements were performed on a Setaram micro-DSC II batch and flow calorimeter. Sample pans contained accurately measured amounts of sample (close to 800 mg). NaCl solutions having the same ionic strength as the samples were used as references. Before each measurement, materials were heated to high temperature to eliminate thermal history effects, then cooled, and heated again at 1 °C/min. Enthalpies of transitions, onset temperatures, and peak maximum temperatures were calculated using Setaram software, which considered baseline subtraction and integration steps. Turbidity Measurements. These were performed on a Shimadzu UV-2101PC UV-vis scanning spectrophotometer in the wavelength range 400-800 nm, for a path length of 1 cm. Solutions and reference samples were filtered (Whatman PUDF filter, 0.45 µm) and added to preheated quartz cuvettes. The latter were equilibrated at 60 °C, cooled to 10 °C at 1 °C/min, and held at 10 °C for 20 min (programmable circulating water bath). Confocal Microscopy. The instrument used was a BioRad MRC 600 confocal scanning laser microscope (Bio-Rad Laboratories). A 0.01% Rhodamine-B solution was added to the hot sample solutions and these were pipetted into preheated single cavity microscope slides, and placed on a Linkam THM 600 temperature-controlled microscope stage at 60 °C. Cooling to 20 °C followed at 1 °C/min. A 568 nm excitation line from a Krypton/Argon mixed gas laser was used to image the sample, emission being collected above 585 nm. A ×60 1.4 na oil immersion objective was used to acquire images at 40 °C or less, a ×20 0.75 na dry objective being used at higher temperatures. Images were collected at approximately 20 µm beneath the cover glass surface. No specific fluorescent labeling of the polymers was attempted. Transmission Electron Microscopy. Gelled samples were cut into 1 mm cubes and immersed in 0.05% ruthenium tetroxide at room temperature for 2 h. The fixed samples were then washed in distilled water and progressively dehydrated using aqueous ethanol solutions of increasing concentration (30 min in 50, 70, 90, 100% solutions). The samples were then resin embedded in LR White/GMA (7:3) for 8 days, using a polymerization temperature of 55 °C. Sectioning was performed using an Ultracut E microtome, and the sections used for counter-staining or antibody labeling. Rabbit anti-agar labeled sections were further treated
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Figure 1. Shear modulus - time cure curves for gellan solutions (I ) 0.066 M) in the concentration range 0.8-1.2% w/w. The applied temperature profile is also indicated.
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Figure 2. Shear modulus-time cure curves for agarose solutions in the concentration range 0.25-1.75% w/w. The temperature profile was as in Figure 1.
with goat anti-rabbit gold conjugates and counterstained with uranyl acetate (10 min) and lead citrate (30 s). Gold conjugates were purchased from British BioCell International, and the antibodies were raised at the Royal Holloway Hospital. Micrographs were recorded using a JEOL 1220 TEM. Results Cure Curve Studies. Shear modulus-time cure curves (G′, G′′ from 60 to 10 °C at 1 °C/min) were measured for gellan solutions at constant (0.066 M) ionic strength as described above. The gelled samples were finally maintained at 10 °C, for a period, to obtain limiting long-time modulus estimates. Results for the concentration series (0.8, 0.9, 1.0, 1.1, and 1.2% w/w) are presented in Figure 1 data being included from 1000 s only. Discontinuities visible in the curves correspond to the ends of the applied temperature ramps. These features, which were much less prominent in agarose cure data (see below), are not produced by slippage but appear to be a consequence of rapid response of the gellan ordering process to temperature, at lower temperatures, and a strong element of reversibility. The concentration dependence of the long-time limiting shear modulus value could be described by a power law function (exponent 2.6) but was also consistent with a previously published cascade4,8-11 network model (continuously varying power law) and an extrapolated critical concentration Co ) 0.2 ( 0.1% w/w. In the present gellan case, the two models were not easily distinguishable, owing to the limited C/Co experimental range involved. In addition, by following a procedure discussed recently by one of the present authors,12 the cure curves for the different gellan concentrations could be accurately superimposed to give a master curve. This involved calculating axial shifts relative to a reference cure curve (log-log display) at intermediate sample concentration. The master curve was essential when assessing “effective” concentrations for the gellan in the composite gels, as will be made clear later. In a similar way, shear modulus-time cure curves were obtained for the agarose component, for the concentration
Figure 3. Shear modulus - time cure curves for mixtures at constant gellan (1.2% w/w) content, and agarose concentration in the range 0.25-1.0% w/w. Temperature profile was as for the pure components (Figures 1 and 2).
series 0.25, 0.5, 0.75, 1.0, 1.25, 1.5, and 1.75% w/w. These results appear in Figure 2. Again the long-time limiting modulus values could be described by a power law (exponent 2.7) but less well than in the gellan case, probably because of the wider C/Co range involved. A corresponding cascade analysis predicted a Co value of 0.07 ( 0.01%w/w, but the overall fit obtained for the agarose data was not as good as usually obtained for biopolymer gels using this approach. As for gellan, reduction of the cure data at different concentrations allowed good superposition to master curve form. Cure curves were measured for gellan-agarose mixtures at three fixed gellan concentrations (0.8, 1.0, and 1.2% w/w) and, in each case, for a series of added agarose concentrations. Gelation conditions were as for the individual components. Some typical results for the gellan 1.2% w/w/ agarose (0.25-1.0% w/w) mixtures are shown in Figure 3. These cure curves all display an initial “shoulder” corresponding to the gellan gelling first during the temperature scan (see DSC evidence below). The subsequent increases in modulus correspond to agarose gelation. Further analysis of these data in terms of implied “effective” concentrations
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Figure 4. Stress-strain large deformation compression data for a pure 1.2% w/w gellan gel system and for its gelled mixtures containing agarose (0.35-1.0% w/w). For the thermal history of the gels, see text.
for the components and the additivity of their individual modulus contributions will be postponed until the Discussion. Large-Deformation Compression Measurements. Stressstrain compression data for the pure 1.2% w/w gellan system and for mixtures containing 1.2% w/w gellan and a series of added agarose concentrations (0.35% - 1.0% w/w) are shown in Figure 4. The individual curves tend to be concave upward and can be roughly divided into two linear regions, the second steeper than the first, indicating strain-hardening. All the gels show brittle failure at very similar strains and at a strain slightly greater than for pure agarose gels alone. The stress at failure increases substantially as the agarose concentration increases, which is not surprising in view of the increased modulus of the materials on increasing agarose content. Interestingly, estimates of the compression modulus from the initial linear regions of the stress-strain curves could be accurately expressed as simple sums of similar estimates for gels based on the single polymer components at corresponding concentrations. The agarose evidently reenforces the gellan network in a straightforward way, without radically changing its failure mechanism or the strain at which it fails. This is in contrast to what is found for phaseseparated emulsion gels where larger changes in material properties (in relation to the components) are sometimes observed.13 Differential Scanning Calorimetry. DSC traces, obtained on both cooling and heating a 1.2% w/w gellan solution, are shown in Figure 5. In line with previous literature14,15 on gellan thermal behavior, these provide clear evidence for a cooperative helix-coil transition during the cooling stage (sharp exotherm) while, on heating, the rather different gel melting curve shows that the helices have also aggregated (a much less cooperative process). This is an example of the well-known hysteresis property of certain polysaccharide gels, where the melting endotherm effects occur at higher temperatures, and are less well resolved, than the single fairly sharp exotherms found on cooling. Melting of the helix aggregates occurs at higher temperatures than the much more cooperative helix-coil transition, and is accompanied by spontaneous helix melting as the helices are released. The existence of more than one (partly) resolvable melting event
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Figure 5. Differential scanning calorimetry data (cooling and heating curvesssee text) for 1.2% w/w gellan (I ) 0.066 M) and 0.85% w/w agarose. Scan rate 1 °C/min.
Figure 6. Differential scanning calorimetry data (cooling and heating) for a gellan (1.2% w/w) and agarose (0.85% w/w) mixture (I ) 0.066 M). Scan rate: 1 °C/min.
for gellan, suggested by the melting DSC data, is consistent14 with the mixed ion character of the commercial sample used. DSC data also appears in Figure 5 for an 0.85% w/w agarose system. Here, as for gellan, the cooling scan shows a single exothermic peak associated with helix formation, but the melting endotherm extends to much higher temperature, in a manner insensitive to scan rate, and shows the effects of aggregate (and consequent helix) melting spread out over a sizable temperature range. Network building by both commercial gellan and agarose involves helix-helix association (formation of ordered fibrous networks) with the enthalpy of this aggregation process made difficult to determine by the apparent lack of cooperativity involved and a fairly strong background contribution from helix melting. The situation for gellan-agarose mixtures appears in Figure 6, for the combination gellan 1.2% w/w and agarose 0.85% w/w. Two well-defined exothermic peaks are found on cooling, and these correspond closely to the positions and sizes of the peaks expected for the pure components; i.e., the helix-coil transitions seem unaffected in the mixture, with the gellan ordering first. This conclusion was strengthened by quantitative examination of the integrated enthalpies where accurate additivity was found. Similar results were found from measurements made at other agarose concentra-
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Figure 7. Evolution of turbidity with time for a cooled 1.2% w/w gellan solution, and for its mixtures with increasing amounts of agarose. For the temperature profile, see text.
tions considered in this work (range 0.4-1.0% w/w) and for lower gellan concentrations (0.8 and 1.0% w/w). There is thus little evidence that, under the concentration and fixed ionic strength conditions adopted in this study, any new helical structure involving cross association of the two polymer types, is involved or indeed that one polymer has a significant influence on the structure, or stability, of the helix formed by the other. The results do not, however, completely exclude interaction between gellan and agarose helices, particularly as the melting data for the mixtures cannot be represented exactly by simple summation. The discrepancies involved suggest, at the very least, that the distribution of helix bundle thickness, particularly for agarose, has been influenced by the mixed biopolymer environment and could even suggest some form of cross-helix interaction (formation of a “coupled” network16). The latter interpretation seems highly unlikely, however, when all the experimental data and their interpretation are taken into account (see Discussion). Turbidity Measurements. Evolution of the turbidity with time for the pure 1.2% w/w gellan system and for mixtures with increasing agarose content appear in Figure 7 and, like the modulus cure curves, show features which can be identified with gelling of the individual components. Network formation by gellan produces only a small turbidity change (see pure gellan result) and is identifiable with the first turbidity increase in the figure. The agarose contribution which follows is much larger. Reference to pure agarose gel turbidity measurements (not shown) demonstrates that the final turbidity levels reached are generally less than would be expected on the basis of simple additivity. This is not unexpected, as the pore size of the mixed system network structure (and hence correlation length) is likely to be smaller than for the agarose network alone, especially if a form of molecularly interpenetrating network (IPN) is involved. There is the additional possibility, suggested by the DSC data, that the agarose network strand (helix bundle) thickness distribution has itself been somewhat changed in the mixed gel environment. This too would have a bearing on turbidity. What is clear from the results, however, is that no simple phase separation process is involved, as the turbidity (probably initially and certainly finally) would be expected to be
Figure 8. Transmission electron micrograph for a 1.2% w/w gellan gel. Image width: 6 µm.
Figure 9. Transmission electron micrograph for a 1.5% w/w agarose gel. Image width: 6 µm.
much larger for the mixtures than is found. More quantitative modeling of the turbidity data will not be attempted here, as light scattering from gel networks of the kind encountered in this study, involves a complex combination of scattering
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Figure 11. Composite shear moduli based on polymer nominal concentrations and simple additivity of component contributions (open symbols) are compared with corresponding experimental data (closed symbols) for two gellan-agarose series (gellan fixed, agarose increasing).
Figure 10. Transmission electron micrograph for the 1.2% w/w/1.5% w/w gellan-agarose composite gel. The agarose network has been specifically highlighted (see starred regions) using rabbit antibody and gold conjugate labeling. Image width: 6 µm.
from the individual polydisperse component fibers (form factor) and the mutual interference of these scattering events, based on the organization of the fibers (structure factor) in space. Too many unknown parameters would be involved in such an exercise. Microscopy. No evidence for phase separation at a micrometer level was found for the mixtures (sols or gels) using the confocal approach (rhodamine staining only) described earlier, and this conclusion of essential homogeneity of the mixed systems was strongly confirmed by transmission electron microscopy. Figures 8-10 show micrographs for 1.2% w/w gellan, 1.5% w/w agarose, and the corresponding mixed system. These transmission electron micrographs are typical of the entire gel network structures and seem to provide strong evidence of molecular interpenetration of agarose and gellan networks, possibly with some change in the levels of helix aggregation and organization within the individual networks. This is suggested both by the general appearance of the networks in the micrographs, and by the distribution of agarose in the mixed system made just visible in Figure 10 by additional antibody-gold conjugate labeling (black dots). Similar results were obtained at lower agarose and gellan concentrations, specificity of the agarose labeling being checked by appropriate controls (e.g., labeling studies of the pure gellan systems). Discussion The simplest hypothesis to explain the above findings is that the gellan-agarose system provides a good example of
a molecular IPN. The two components appear to form their own individual ordered conformations at the appropriate temperatures (in relation to conditions of ionic strength, temperature scan rate, etc.) and aggregate into network structures similar to those formed in isolation. Furthermore, there is strong evidence from the microscopy and turbidity data that, rather than existing in separate regions of space (microphase or simple phase separation), the two networks interpenetrate on a molecular length scale, one network essentially passing through the pores of the other. For the molecular IPN, in contrast to the situation for a truly phase-separated system,4,17 the idea of an effective (i.e., local) concentration different from nominal seems meaningless, and doubts arise about how to relate composite properties to the behavior of the individual gelling components. Indeed, at the simplest level, in the molecular IPN case, one might regard effective concentrations as the same as nominal, since in no sense does real segregation (and mutual concentration) occur, and propose simple addition for combining modulus contributions. However, as the comparison between this simple approach and experiment presented in Figure 11 shows, this is only a rough approximation, whose underlying assumptions require appraisal. For example, in relation to the use of nominal polymer concentrations, if the behavior of a polymer component in an IPN, such as its gelling capacity in relation to concentration, is to be compared to its modulus-concentration behavior as a single component in solution, it should be remembered that, in the mixture, the solvent is not pure water or even a simple salt solution. It obviously contains a proportion of the other polymer, either in coil form or as aggregates or even as a gel network. This compositional effect, which was discussed at length in the previous gellanPaselli SA2 paper,6 is likely to imply a change in gelling parameters, such as the rate constants for cross-linking and/ or the front factor, which is a measure of network strand rigidity, and/or the functionality (potential number of crosslinking sites per aggregating species). In the IPN situation, the main implication of changing these gelling parameters for either biopolymer component, is a change in its natural critical gelling concentration Co
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when present under the mixed system conditions.4 One must therefore accommodate this change in any model relating the mixed gel properties of IPNs to the gelling properties of the individual components. One approach would be to take the appropriate property-concentration relationship (modulus, gel time, etc.) for a component as measured in solution on its own, and displace this horizontally (in log-log form) by the log of the ratio of new-to-old critical concentrations involved (master curve property). In principle, one could then use this new relationship to calculate the contribution to the IPN made by the component at its nominal concentration. An alternative, and equivalent, strategy,6 however, which is more useful in practice, and which remains analogous to the current approach to phase-separated systems,4,17 is to recognize that shifting the property-concentration relationship in log space for a given polymer component (in “pure” form) is quantitatively the same as assuming the pure component property relationship is still applicable and displacing all nominal concentrations by the same amount, but in the opposite direction along the concentration axis. The required critical concentration ratio is thus equivalent to the reciprocal of a ratio involving an apparent or “effective” concentration for the component in the mixture and its true, i.e., nominal, concentration. This effective concentration has no real physical significance of course, in the sense of being a measure of component density in space, but much as has been done for truly segregated systems,4,17 where it has such a meaning, it can be used to calculate component contributions to composite behavior from data for the single polymer gels. To quantify this effect for IPNs, it was suggested in the previous gellan-Paselli SA2 article6 that, for either polymer component, its new effective concentration could be related to both its own nominal concentration and that of the other polymer, through series expansions of the form m2′ ) m2(1 + k1m3 + k2m32 + ...)
(1)
m3′ ) m3(1 + q1m2 + q2m22 + ...)
(2)
and
derived directly from corresponding expansions6 for the perturbed critical concentrations of the gelling species. Here m denotes concentration in mass fraction, 2 and 3 denote polymer components 2 and 3, and m2′ and m3′ are effective concentrations, as distinct from m2 and m3, which are nominal concentrations. The coefficients k1, k2, etc and q1, q2, etc, which also appear above and can be assumed to be unrelated, define the series expansions and, for the present, are essentially empirical. For the model to be useful, however, i.e., to have sufficiently few parameters, higher values of these coefficients should preferably be negligibly small, with the linear first term dominant. Evidently, from eqs 1 and 2, the ratios m2′/m2 and m3′/m3 are independent of the nominal concentrations m2 and m3, respectively. This means that effective concentration data for more than one nominal concentration of the polymer component of interest and, in each case, for a series of values of the nominal concentration of the other “solvent” polymer
ought to superimpose when appropriately normalized. Interestingly, this is not expected to be true for segregated systems where the effective concentrations relate differently6 to the nominal values and indeed are not independent of one another. The current model thus implies that, in addition to the lack of a relationship between effective concentrations for the polymer components in a molecular IPN, this superposition property is also a signature of the molecular IPN condition and allows it to be distinguished from the more common simple phase-separated situation. Since the effective concentrations are not real (but a useful mathematical construct), methods such as FTIR, Raman, and fluorescence spectroscopy18-20 aimed at direct concentration measurement, through estimating amounts of material in a local region of space, are obviously inappropriate. Instead, one must focus on properties which, at constant concentration, can vary with the gelling parameters, i.e., properties that can be used as sensitive probes of these. In the previous work6 on Paselli-SA2, it was suggested that the rise times of modulus cure curves (i.e., gel times) or turbidity-time curves were optimal for this purpose, provided that they could be established without deconvolution difficulties or ambiguities arising from the assumption of specific additivity laws. In the present case, however, not only do the gellan and agarose processes (modulus and turbidity increases) overlap more closely than for gellan-SA2, making their deconvolution less certain, but also the changes in gel times in relation to pure system behavior are very small, making the sensitivity of the approach rather low. In the event, in the present case, a slightly different approach to effective concentration estimation was adopted, using the initial part of the modulus-time cure curve and focusing on the amplitude of the gellan contribution “shoulder”, rather than its “rise time”. For all mixture modulustime data, this shoulder was fitted using the cure master curve for the pure gellan system (see earlier section), and a longtime modulus contribution for the gellan in the mixture was assessed. This could be interpreted as the long-time modulus value the gellan component would have achieved if the agarose had failed to order. Such focus on the modulus contribution rather than the “rise time” or gel time requires caution, however, as its success as a means of estimating effective concentrations is based on at least two assumptions, both relating to whether deconvolution and additivity problems are involved. The first is that the agarose contribution to the shoulder must be negligible around the time at which the shoulder value is achieved and measured. The second is the assumption that real phase separation is not involved since, for a truly phase-separated system, the shoulder height could vary considerably with the phase morphology of the developing composite. Adopting these assumptions in the present case, the estimate of a long time modulus contribution from the gelling gellan can be converted to an effective gellan concentration using the modulus-concentration data for the pure system (much as could be done for the gel time). In the present gellan case, since a certain amount of extrapolation of the experimentally available modulus data to higher concentrations was required, a cascade description4,9-11 for the
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Figure 12. Plots of reduced gellan effective concentration (ratio m2′/ m2 in text) versus agarose nominal concentration (m3 in text). The effective concentration data has been normalized by dividing by the appropriate gellan nominal (m2) concentration values (0.8 (9), 1.0 (b), and 1.2% (∆) w/w). The best fitting straight line constrained to pass through 1.0 at zero nominal agarose concentration is also shown.
modulus-concentration relationship was adopted, rather than the simple power law. Past experience suggests that the latter is unable to describe modulus-concentration data for biopolymer gels over a wide concentration (C/Co) range. Final results for the gellan effective concentrations reduced by dividing by the corresponding nominal concentration values, i.e., m2′/m2 as suggested by eq 1, are plotted against nominal agarose concentrations in Figure 12. When doing this, the nominal gellan concentration values were added as data points at zero added agarose. The three data sets superimpose fairly well, as predicted by the model, and the relationship is close to linear. Indeed a gradient parameter k1 ) 0.52 (0.03) can be obtained by least-squares fitting (straight line constrained to pass through 1.0 for zero nominal agarose concentration). Clearly, the nominal gellan concentration is expected to increase by a factor of some 1.5 over the range of nominal agarose concentrations considered. This is a significant if not enormous effect and implies some enhancement of the gellan gelling capacity in the presence of agarose. Unfortunately, it is impossible in the present case to correspondingly determine effective concentrations for the agarose component from the cure data. This would require deconvolution of these data based on assumptions about how to add the individual polymer network modulus contributions. As this is one of the things one would like to determine using the effective concentrations, its assumption to obtain effective concentrations, involves an obvious circularity. In the former gellan-Paselli SA2 case a similar problem was found,6 but there, turbidity-time measurements were quite well resolved, and were dominated by the SA2 contribution. They therefore provided independent evidence about the SA2 effective concentration values. For the present system a similar option is unavailable. Perhaps all one can say is that if the simplest assumption about such additivity were to be made (simple summation) and the previous gellan effective concentrations were assumed, the agarose effective concentrations would be close to nominal. In summary, the present paper has provided a range of evidence for molecular IPN formation in gellan-agarose
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mixtures. Although, in the past, a phase-separated description has been applied to at least one type of gellan-agarose combination,21 a simple phase-separated microstructure can be rejected in the present case. The weight of evidence favors independent network formation by the two components and interpenetration on a molecular length scale (at least under the concentration and ionic strength conditions studied). While some direct coupling between the networks at a helixto-helix level cannot be completely ruled out, there is little evidence for this, and the independent molecular IPN provides the simplest interpretation of the available data. Some changes in the gellan gelling parameters are suggested, however, by the increased gellan effective concentrations obtained by analysis of cure curve data, and the dependence of this effect on the agarose nominal concentration can be described consistently using a previously published model. This model retains as a principle the idea of relating overall composite properties to individual component behavior, but this is more difficult to achieve for IPNs than for more conventional segregated systems, as it requires introduction of a rather abstract “effective concentration”. Ultimately, for nonsegregated gels, the link to single component behavior may have to be abandoned in favor of a more direct address of how one polymer interacts with the aggregation and gelling of another. In large deformation terms, the influence of agarose added to gellan, and under conditions where the gellan gels first, is to re-enforce the network (higher compression and shear modulus) without changing the strain-to-break or the brittle failure characteristics of the failure mechanism. Acknowledgment. The authors thank colleagues at the Colworth Laboratory for many helpful discussions of polysaccharide gelation and the implications of IPN network formation. They also thank Mr. D. Ferdinando for assistance with confocal microscopy and Miss A. Russell for molecular weight determination. References and Notes (1) Biopolymer Mixtures; Harding, S. E., Hill, S. E., Mitchell, J. R., Eds.; Nottingham University Press: Nottingham, England, 1995. (2) Clark, A. H.; Richardson, R. K.; Robinson, G.; Ross-Murphy, S. B.; Weaver, A. C. Prog. Food Nutr. Sci. 1982, 6, 149-160. (3) Clark, A. H.; Richardson, R. K.; Ross-Murphy, S. B.; Stubbs, J. M. Macromolecules 1983, 16, 1367-1374. (4) Clark, A. H. In Food Structure and BehaViour; Lillford, P. J., Blanshard, J. M. V., Eds.; Academic Press: London, 1987; pp 1334. (5) Picullel, L.; Bergfeldt, K.; Nilsson, S. In Biopolymer Mixtures; Harding, S. E., Hill, S. E., Mitchell, J. R., Eds.; Nottingham University Press: Nottingham, England, 1995; pp 13-35. (6) Clark, A. H.; Eyre, S. C. E.; Ferdinando, D. P.; Lagarrigue, S. Macromolecules 1999, 32, 7897-7906. (7) Morris, V. J. In Functional Properties of Food Macromolecules, 2nd ed.; Hill, S. E., Ledward, D. A., Mitchell, J. R., Eds.; Aspen Publishers Inc.: Gaithersburg, MD, 1998; pp 188-195. (8) Gordon, M.; Ross-Murphy, S. B. Pure Appl. Chem. 1975, 43, 1-26. (9) Clark, A. H.; Ross-Murphy, S. B. Br. Polym. J. 1985, 17, 164-168. (10) Clark, A. H. Polym. Networks 1993, 1, 139-158. (11) Clark, A. H.; Farrer, D. B. J. Rheol. 1995, 39, 1429-1444. (12) Normand, V.; Muller, S.; Ravey, J.-C.; Parker, A. Macromolecules 2000, 33, 1063-1071. (13) Plucknett, K. P.; Normand, V.; Pomfret, S. J.; Ferdinando, D. Polymer 2000, 41, 2319-2323. (14) Watase, M.; Nishinari, K. Food Hydrocolloids 1993, 7, 449-456.
Gellan-Agarose Gel Composites (15) Miyoshi, E.; Takaya, T.; Nishinari, K. Food Hydrocolloids 1994, 8, 529-542. (16) Morris, E. R. In Biopolymer Mixtures; Harding, S. E., Hill, S. E., Mitchell, J. R., Eds.; Nottingham University Press: Nottingham, England, 1995; pp 247-288. (17) Kasapis, S. In Biopolymer Mixtures; Harding, S. E., Hill, S. E., Mitchell, J. R., Eds.; Nottingham University Press: Nottingham, England, 1995; pp 193-224. (18) Durrani, C. M.; Prystupa, D. A.; Donald, A. M.; Clark, A. H. Macromolecules 1993, 26, 981-987.
Biomacromolecules, Vol. 1, No. 4, 2000 729 (19) Durrani, C. M.; Donald, A. M. Carbohydr. Polym. 1995, 28, 297303. (20) Blonk, J. C. G.; Van Eendenberg, J.; Koning, M. M. G.; Weisenborn, P. C. M.; Winkel, C. Carbohydr. Polym. 1995, 28, 287-295. (21) Nishinari, K.; Takaya, T.; Watase, M. In Food Hydrocolloids: Structures, Properties, and Functions; Nishinari, K., Doi, E., Eds.; Plenum Press: New York, 1994; pp 473-476.
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